The most common perception is that customization and personalization are one and the same thing. But in the era of the personal (big) data the term personalization has evolved and became something different. ​

Data Analytics Driven Personalization

While customization is tailored by subjective desires and that what seams most convenient to the user, personalization is more objective and data driven. Customization is something that user specifies according to the perceived needs or habits. On the other hand, personalization is something tailored for the user by analyzing all the relevant data and all about finding the perfect, sweet spot for him.

In the case of customization users do all the work by the feeling or experience and have to setup everything by themselves. But in the case of personalization, users just enjoy the ride and let the data they create do the entire job of finding what setup is the most efficient or according to exact needs. But that’s not all. Data driven personalization enables us to find out hidden patterns and anomalies, usually not visible by the plain observation or experience.

We can make a perfect example in the fitness domain. Since we are all different, have different potential, physical talents and fitness level, we cant have the same training plan that is working efficiently for two people. But nowadays training plans are made just according to the goals and expectations that a trainee has. Okay, every responsible fitness instructors take into the account age and weight of the trainee when making a training plan. But all of us can work just with the data available to us.

How can we personalize the training plan, and tailor it to perfectly fit the trainee?

Well,  is in the data-analytics driven personalization.

The key role of the data analytics is to provide the fitness instructor invaluable guidelines how to create the most effective, motivating and therefore satisfying training plan for the trainee customers. Also the data analytics is the perfect method for spotting any trends in the training behavior of the trainee customers. For instance, if the trainee’s strength, or endurance or overall performance during the training is going down, professional instructor must change something to stop this negative trend and if it is going up, he must continue to use what works well for that person.

One of the most important role of the data analytics, is to eliminate too many variations in the training performance of trainees. Only when trainings are performed in the stable way, without any variations, the doors open for the improvement. Only then the true progress and performance of the trainee becomes visible and efficient.